Hans Matter

Sanofi Aventis Group, Lutetia Parisorum, Île-de-France, France

Are you Hans Matter?

Claim your profile

Publications (63)232.3 Total impact

  • Toxicology Letters 09/2014; 229, Supplement:S164. · 3.36 Impact Factor
  • Source
    Journal of Cheminformatics 03/2014; 6(Suppl 1):O10. · 4.54 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Drug action can be rationalized as interaction of a molecule with proteins in a regulatory network of targets from a specific biological system. Both drug and side effects are often governed by interaction of the drug molecule with many, often unrelated, targets. Accordingly, arrays of protein-ligand interaction data from numerous in vitro profiling assays today provide growing evidence of polypharmacological drug interactions, even for marketed drugs. In vitro off-target profiling has therefore become an important tool in early drug discovery to learn about potential off-target liabilities, which are sometimes beneficial, but more often safety relevant. The rapidly developing field of in silico profiling approaches is complementing in vitro profiling. These approaches capitalize from large amounts of biochemical data from multiple sources to be exploited for optimizing undesirable side effects in pharmaceutical research. Therefore, current in silico profiling models are nowadays perceived as valuable tools in drug discovery, and promise a platform to support optimally informed decisions.
    Future medicinal chemistry 03/2014; 6(3):295-317. · 4.00 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Abstract The electron transport chain (ETC) couples electron transfer between donors and acceptors with proton transport across the inner mitochondrial membrane. The resulting electrochemical proton gradient is used to generate chemical energy in the form of adenosine triphosphate (ATP). Proton transfer is based on the activity of complex I-V proteins in the ETC. The overall electrical activity of these proteins can be measured by proton transfer using Solid Supported Membrane technology. We tested the activity of complexes I, III, and V in a combined assay, called oxidative phosphorylation assay (oxphos assay), by activating each complex with the corresponding substrate. The oxphos assay was used to test in-house substances from different projects and several drugs currently available on the market that have reported effects on mitochondrial functions. The resulting data were compared to the influence of the respective compounds on mitochondria as determined by oxygen consumption and to data generated with an ATP depletion assay. The comparison shows that the oxidative phosphorylation assay provides both a rapid approach for detecting interaction of compounds with respiratory chain proteins and information on their mode of interaction. Therefore, the oxphos assay is a useful tool to support structure activity relationship studies by allowing early identification of mitotoxicity and for analyzing the outcome of phenotypic screens that are susceptible to the generation of mitotoxicity-related artifacts.
    Assay and Drug Development Technologies 08/2013; · 2.08 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: We have used a set of four local properties based on semiempirical molecular orbital calculations (the electron density (ρ), hydrogen bond donor field (HDF), hydrogen bond acceptor field (HAF) and molecular lipophilicity potential (MLP)) for 3D-QSAR studies to overcome the limitations of the current force-field based molecular interaction fields (MIFs). These properties can be calculated rapidly and are thus amenable to high-throughput industrial applications. Their statistical performance was compared with that of conventional 3D-QSAR approaches using nine datasets (angiotensin converting enzyme inhibitors (ACE), acetylcholinesterase inhibitors (AchE), benzodiazepine receptor ligands (BZR), cyclooxygenase-2 inhibitors (COX2), dihydrofolate reductase inhibitors (DHFR), glycogen phosphorylase b inhibitors (GPB), thermolysin inhibitors (THER), thrombin inhibitors (THR) and serine protease factor Xa inhibitors (fXa)). The 3D-QSAR models generated were tested thoroughly for robustness and predictive ability. The average performance of the quantum mechanical molecular interaction field (QM-MIF) models for the nine datasets is better than that of the conventional force-field-based MIFs. In the individual datasets, the QM-MIF models always perform better than, or as well as, the conventional approaches. It is particularly encouraging that the relative performance of the QM-MIF models improves in the external validation. In addition, the models generated showed statistical stability with respect to model building procedure variations such as grid spacing size and grid orientation. QM-MIF contour maps reproduce the features important for ligand binding for the example dataset (factor Xa inhibitors), demonstrating the intuitive chemical interpretability of QM-MIFs.
    Journal of Chemical Information and Modeling 05/2013; · 4.30 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: A novel procedure for in-silico rescaffolding and side chain optimization is reported with explicit consideration of the route of chemical synthesis and availability of compatible chemical reagents. We have defined a set of retrosynthetic disconnections representing robust chemical reactions, amenable for combinatorial chemistry. This rule set is used to generate virtual fragment databases from available chemical reagents. Each reactive center is annotated with its compatibility with regard to the chemical reactions. The rule set is then applied to a new molecule to obtain separate query subunits for rescaffolding by 3D shape matching in specific reagent-derived fragment databases. Thus, only fragment hits compatible with the chemistry and shape of the corresponding query moiety are investigated further. The identified fragment hits directly indicate (1) available chemical reagents that can replace the query moiety in the starting molecule and (2) the route for the synthesis of the proposed molecules.
    Journal of Medicinal Chemistry 04/2013; · 5.48 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Stearoyl-CoA desaturase (SCD1) is linked to the pathogenesis of obesity, dyslipidemia and type 2 diabetes. It is the rate-limiting enzyme in the synthesis of monounsaturated 16:1 n-7 and 18:1 n-9 fatty acyl-CoAs and catalyses an essential part of lipogenesis. Here, we describe the identification, in vitro properties and in vivo efficacy of a novel class of heterocyclic small molecule hexahydro-pyrrolopyrrole SCD1 inhibitors. SAR707, a compound representative for the series, was optimised to high in vitro potency, selectivity and favourable overall properties in enzymatic and cellular assays. In vivo, this compound reduced serum desaturation index, decreased body weight gain and improved lipid parameters and blood glucose levels of obese Zucker diabetic fatty rats treated for 4 weeks in a chronic study. In parallel, fissures of the eye lid, alopecia and inflammation of the skin were observed from day 11 on in all animals treated with the same metabolically active dose. In summary, we described in vitro and in vivo properties of a novel, potent and selective SCD1 inhibitor that improved body weight, blood glucose and triglycerides in an animal model of obesity, type 2 diabetes and dyslipidemia. However, the favourable in vivo properties of systemic SCD1 inhibition shown in our study were accompanied by dose-dependently occurring adverse target-related effects observed in skin. Thus, systemic SCD1 inhibition by small molecules might therefore not represent a feasible approach for the treatment of chronic metabolic diseases.
    European journal of pharmacology 03/2013; · 2.59 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: The discovery of potent benzimidazole stearoyl-CoA desaturase (SCD1) inhibitors by ligand-based virtual screening is described. ROCS 3D-searching gave a favorable chemical motif that was subsequently optimized to arrive at a chemical series of potent and promising SCD1 inhibitors. In particular, compound SAR224 was selected for further pharmacological profiling based on favorable in vitro data. After oral administration to male ZDF rats, this compound significantly decreased the serum fatty acid desaturation index, thus providing conclusive evidence for SCD1 inhibition in vivo by SAR224.
    Bioorganic & medicinal chemistry letters 01/2013; · 2.65 Impact Factor
  • Chemoinformatics for Drug Discovery, Edited by J. Bajorath, 01/2013: chapter 10; Wiley., ISBN: 9781118742785
  • Chemoinformatics for Drug Discovery, Edited by J. Bajorath, 01/2013: chapter 11; Wiley., ISBN: 9781118742785
  • [Show abstract] [Hide abstract]
    ABSTRACT: Current 3D-QSAR methods such as CoMFA or CoMSIA make use of classical force-field approaches for calculating molecular fields. Thus, they can not adequately account for noncovalent interactions involving halogen atoms like halogen bonds or halogen-π interactions. These deficiencies in the underlying force fields result from the lack of treatment of the anisotropy of the electron density distribution of those atoms, known as the "σ-hole", although recent developments have begun to take specific interactions such as halogen bonding into account. We have now replaced classical force field derived molecular fields by local properties such as the local ionization energy, local electron affinity, or local polarizability, calculated using quantum-mechanical (QM) techniques that do not suffer from the above limitation for 3D-QSAR. We first investigate the characteristics of QM-based local property fields to show that they are suitable for statistical analyses after suitable pretreatment. We then analyze these property fields with partial least-squares (PLS) regression to predict biological affinities of two data sets comprising factor Xa and GABA-A/benzodiazepine receptor ligands. While the resulting models perform equally well or even slightly better in terms of consistency and predictivity than the classical CoMFA fields, the most important aspect of these augmented field-types is that the chemical interpretation of resulting QM-based property field models reveals unique SAR trends driven by electrostatic and polarizability effects, which cannot be extracted directly from CoMFA electrostatic maps. Within the factor Xa set, the interaction of chlorine and bromine atoms with a tyrosine side chain in the protease S1 pocket are correctly predicted. Within the GABA-A/benzodiazepine ligand data set, PLS models of high predictivity resulted for our QM-based property fields, providing novel insights into key features of the SAR for two receptor subtypes and cross-receptor selectivity of the ligands. The detailed interpretation of regression models derived using improved QM-derived property fields thus provides a significant advantage by revealing chemically meaningful correlations with biological activity and helps in understanding novel structure-activity relationship features. This will allow such knowledge to be used to design novel molecules on the basis of interactions additional to steric and hydrogen-bonding features.
    Journal of Chemical Information and Modeling 08/2012; 52(9):2441-53. · 4.30 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: The pregnane X receptor (PXR), a member of the nuclear hormone superfamily, regulates the expression of several enzymes and transporters involved in metabolically relevant processes. The significant induction of CYP450 enzymes by PXR, in particular CYP3A4, might significantly alter the metabolism of prescribed drugs. In order to early identify molecules in drug discovery with a potential to activate PXR as antitarget, we developed fast and reliable in silico filters by ligand-based QSAR techniques. Two classification models were established on a diverse dataset of 434 drug-like molecules. A second augmented set allowed focusing on interesting regions in chemical space. These classifiers are based on decision trees combined with a genetic algorithm based variable selection to arrive at predictive models. The classifier for the first dataset on 29 descriptors showed good performance on a test set with a correct classification of both 100% for PXR activators and non-activators plus 87% for activators and 83% for non-activators in an external dataset. The second classifier then correctly predicts 97% activators and 91% non-activators in a test set and 94% for activators and 64% non-activators in an external set of 50 molecules, which still qualifies for application as a filter focusing on PXR activators. Finally a quantitative model for PXR activation for a subset of these molecules was derived using a regression-tree approach combined with GA variable selection. This final model shows a predictive r(2) of 0.774 for the test set and 0.452 for an external set of 33 molecules. Thus, the combination of these filters consistently provide guidelines for lowering PXR activation in novel candidate molecules.
    Bioorganic & medicinal chemistry 04/2012; 20(18):5352-65. · 2.82 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: The superadditivity of fragment linking on affinities was quantified by systematic deconstruction of a fXa inhibitor. In their Communication (DOI: 10.1002/anie.201107091), M. Nazaré, H. Matter, and co-workers show that by connecting two fragments with a single bond, a linker contribution of -14.0 kJ mol(-1) results, which corresponds to an affinity improvement of about 2.5 orders of magnitude relative to the sum of fragment affinities.
    Angewandte Chemie International Edition 12/2011; · 11.34 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: More than just the sum of its parts: The superadditivity effect of fragment linking on ΔG was quantified by deconstructing two fXa inhibitors with congeneric fragments, but different linkers. By connecting both fragments with a single bond, a high linker contribution ΔG(link) of -14.0 kJ mol(-1) results, which corresponds to an improvement in affinity by around 2.5 orders of magnitude relative to the sum of fragment ΔG values.
    Angewandte Chemie International Edition 12/2011; 51(4):905-11. · 11.34 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: The optimization of a lead structure to a development candidate often requires removal of undesirable antitarget activities. To this end, we have developed an approach to extract antitarget activity hotspots from larger databases and to transfer this knowledge onto novel chemical series. These antitarget activity hotspots will be captured as pairs of informative molecules, which are chemically closely related, but differ significantly in biological activity. We illustrate the application of antitarget activity hotspots as informative compound pairs for the optimization of side effects in lead structures for relevant antitargets in pharmaceutical research. The use for prospective design requires establishing a structural link between known antitarget hotspot pairs and a new lead structure: we employ 3D-based similarity comparison for this task. The entire workflow serves as idea generator in early optimization. The feasibility of this approach is demonstrated in several optimization problems related to hERG inhibition, and CYP3A4 inhibition. Several structural examples demonstrate the ability of the 3D-shape searching to identify related scaffolds and the usefulness of the antitarget hotspot information to guide optimization by modulating the undesirable antitarget activity. Such a concept based on the analysis of local similarities and the transfer to 3D-related series is especially promising in those cases, where the construction of antitarget QSAR models fails to detect local SAR trends for guiding the next optimization cycle.
    Molecular Informatics 12/2011; 30(11-12):996-1008. · 2.01 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: The selective inhibition of the aspartyl protease renin is of high interest to control hypertension and associated cardiovascular risk factors. Following on preceding contributions, we report herein on the optimization of two series of azaindoles to arrive at potent and non-chiral renin inhibitors. The previously discovered azaindole scaffold was further explored by structure-based drug design in combination with parallel synthesis. This results in the identification of novel 5- or 7-azaindole derivatives with remarkable potency for renin inhibition. The best compounds on both series show IC(50) values between 3 and 8nM.
    Bioorganic & medicinal chemistry letters 09/2011; 21(18):5487-92. · 2.65 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: The control of hypertension and associated cardiovascular risk factors is possible by selective inhibition of the aspartyl protease renin due to its unique position in the renin-angiotensin system. Starting from a previously disclosed series of potent and nonchiral indole-3-carboxamides, we further explored this motif by structure-based drug design guided by X-ray crystallography in combination with efficient parallel synthesis. This resulted in the discovery of 4- or 6-azaindole derivatives with remarkable potency for renin inhibition. The best compound from these series showed an IC(50) value of 1.3 nM.
    Bioorganic & medicinal chemistry letters 09/2011; 21(18):5480-6. · 2.65 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Compounds that simultaneously activate the peroxisome proliferator-activated receptor (PPAR) subtypes PPARγ and PPARδ have the potential to effectively target dyslipidemia and type II diabetes in a single pharmaceutically active molecule. The frequently observed side effects of selective PPARγ agonists, such as edema and weight gain, are expected to be overcome by using partial instead of full agonists for this nuclear receptor family. Herein we report the discovery, synthesis, and optimization of a novel series of sulfonylthiadiazoles that are active as partial agonists. The initial compound 6 was discovered by high-throughput screening as a moderate partial PPARδ agonist; its optimization was based on the X-ray crystal structure in complex with PPARδ. In contrast to other PPARδ agonists, this ligand does not interact directly with residues from the activation helix AF-2, which might be linked to its partial agonistic effect. Interestingly, the thiadiazole moiety fills a novel subpocket, which becomes accessible after moderate conformational rearrangement. The optimization was focused on introducing conformational constraints and replacing intramolecular hydrogen bonding interactions. Highly potent molecules with activity as dual partial PPARγ/δ agonists in the low nanomolar range were then identified. One of the most active members, compound 20 a, displayed EC₅₀ values of 1.6 and 336 nM for PPARδ and γ, respectively. The X-ray crystal structure of its complex with PPARδ confirms our design hypothesis. Compound 20 a clearly displayed in vivo activity in two chronic mice studies. Lipids were modified in a beneficial way in normolipidemic mice, and the development of overt diabetes could be prevented in pre-diabetic db/db mice. However, body weight gain was similar to that observed with the PPARγ agonist rosiglitazone. Hence, active compounds from this series can be considered as valuable tools to elucidate the complex roles of dual PPARγ/δ agonists for potential treatment of metabolic syndrome.
    ChemMedChem 03/2011; 6(4):633-53. · 3.05 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Selective inhibition of the aspartyl protease renin has gained attraction as an interesting approach to control hypertension and associated cardiovascular risk factors given its unique position in the renin-angiotensin system. Using a combination of high-throughput screening, parallel synthesis, X-ray crystallography and structure-based design, we identified and optimized a novel series of potent and non-chiral indole-3-carboxamides with remarkable potency for renin. The most potent compound 5k displays an IC(50) value of 2nM.
    Bioorganic & medicinal chemistry letters 11/2010; 20(21):6268-72. · 2.65 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Attractive chlorine: Noncovalent interactions between chlorine or bromine atoms and aromatic rings in proteins open up a new method for the manipulation of molecular recognition. Substitution at distinct positions of two factor Xa inhibitors improves the free energy of binding by interaction with a tyrosine unit. The generality of this motif was underscored by multiple crystal structures as well as high-level quantum chemical calculations (see picture).
    Angewandte Chemie International Edition 02/2009; 48(16):2911-6. · 11.34 Impact Factor

Publication Stats

944 Citations
232.30 Total Impact Points

Institutions

  • 2013
    • Sanofi Aventis Group
      Lutetia Parisorum, Île-de-France, France
  • 2007
    • University of Tuebingen
      • Institute of Inorganic Chemistry
      Tübingen, Baden-Wuerttemberg, Germany
  • 2006
    • Novartis
      Bâle, Basel-City, Switzerland
  • 2004
    • University of New Mexico
      Albuquerque, New Mexico, United States
  • 1999
    • University of Wuerzburg
      Würzburg, Bavaria, Germany